Bibliographic record
Abstract
Discussion is rampant amongst libraries and information industries about what is Web 2.0.One thing, I believe, is clear now; Web 2.0 isn't a standard in almost any sense of the word.Most concepts behind this term are constructive, building on today's best and improving for the future.Stephen Abram suggested in his recent Information Outlook article that Web 2.0 is about the more human aspects of interactivity on the Web: "It is about conversations, interpersonal networking, personalization and individualism" [1].Frequently, our users want to experience the Web; they want to learn and succeed.And we have to provide the tools and context so they can do just that.As the technology infrastructure of Web 2.0 is still complex and constantly evolving, Web 2.0 is ultimately a social phenomenon of users' experience of the Web and is characterized by open communication, decentralization of authority, and freedom to share and re-use Web content.Many new technologies are emerging under the Web 2.0 umbrella: really simple syndication (RSS), wikis, weblogs, comments functionality, Web personalization, photo sharing (Flickr, Zooomr), social networking software, AJAX and API programming (Google maps), streaming media, podcasting and MP3 files, social bookmarking, open source software, user driven ratings, and open access content.My intent is to discuss some of these technologies and to see how we, as health sciences librarians and medical librarians, can integrate them into our daily practice.I started this series of articles by covering RSS use in medicine [2].In this installment I am discussing weblogging and podcasting.If you are interested, please see my coverage of social networking and social bookmarking and tagging in the next issue of the Journal of the Canadian Health Libraries Association.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.082 | 0.029 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".